English

ARM 4-BIT PQ: SIMD-based Acceleration for Approximate Nearest Neighbor Search on ARM

Machine Learning 2022-03-08 v1 Computer Vision and Pattern Recognition Information Retrieval

Abstract

We accelerate the 4-bit product quantization (PQ) on the ARM architecture. Notably, the drastic performance of the conventional 4-bit PQ strongly relies on x64-specific SIMD register, such as AVX2; hence, we cannot yet achieve such good performance on ARM. To fill this gap, we first bundle two 128-bit registers as one 256-bit component. We then apply shuffle operations for each using the ARM-specific NEON instruction. By making this simple but critical modification, we achieve a dramatic speedup for the 4-bit PQ on an ARM architecture. Experiments show that the proposed method consistently achieves a 10x improvement over the naive PQ with the same accuracy.

Keywords

Cite

@article{arxiv.2203.02505,
  title  = {ARM 4-BIT PQ: SIMD-based Acceleration for Approximate Nearest Neighbor Search on ARM},
  author = {Yusuke Matsui and Yoshiki Imaizumi and Naoya Miyamoto and Naoki Yoshifuji},
  journal= {arXiv preprint arXiv:2203.02505},
  year   = {2022}
}

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ICASSP 2022

R2 v1 2026-06-24T10:02:38.904Z